Object-based Wetland Characterization Using Radarsat-2 Quad-Polarimetric SAR Data, Landsat-8 OLI Imagery, and Airborne Lidar-Derived Geomorphometric Variables

2017 ◽  
Vol 83 (1) ◽  
pp. 27-36 ◽  
Author(s):  
StevenE. Franklin ◽  
OumerS. Ahmed
Keyword(s):  
Airborne Lidar ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Polarimetric Sar ◽  
Object Based ◽  
Sar Data

scholarly journals Analysis of the utilization of landsat 8 oli imagery for mapping the distribution of coral reefs in Pulau Weh Sabang

DEPIK ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 161-166
Author(s):  
M Taufik Rahmadi ◽  
Sugiharto Sugiharto ◽  
Mbina Pinem ◽  
Ayu Suciani
Keyword(s):  
Coral Reef ◽  
Distribution Area ◽  
Landsat 8 ◽  
Nearest Neighbour ◽  
Landsat 8 Oli ◽  
Coral Reef Ecosystem ◽  
Object Based ◽  
Coral Reef Ecosystems ◽  
Almost All ◽  
Reef Ecosystem

As one of the largest archipelagic countries globally, Indonesia has diverse natural resources, one of which is the coral reef ecosystem. Coral reef ecosystems are spread across almost all Indonesian waters, and Pulau Weh Sabang is one distribution area. This study aims to determine the distribution of coral reef ecosystems and test landsat 8 oli imagery accuracy in mapping coral reef ecosystems. The method used in this research is the nearest neighbour algorithm object-based classification method. The results showed that the coral reef ecosystem in Pulau Weh Sabang was divided into two classes: a healthy coral reef ecosystem class with 277.38 hectares and a medium condition coral reef ecosystem class with an area of 710.01 Ha.Keywords:Landsat 8 oliMappingDistributionCoral reefWeh Island 

scholarly journals Detecting the burned area in southern Kalimantan by using the sentinel-1 polarimetric SAR and landsat-8 OLI optic

2020 ◽  
Vol 1528 ◽  
pp. 012048
Author(s):  
I Prasasti ◽  
KIN Rahmi ◽  
JT Nugroho ◽  
J Sitorus ◽  
R Arief ◽  
...  
Keyword(s):  
Burned Area ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Polarimetric Sar

Classification of Polarimetric SAR Data Based on Object-Based Multiple Classifiers for Urban Land-Cover

2016 ◽  
Vol 44 (6) ◽  
pp. 855-863 ◽  
Author(s):  
Masoud Habibi ◽  
Mahmod Reza Sahebi ◽  
Yasser Maghsoudi ◽  
Shaheen Ghayourmanesh
Keyword(s):  
Land Cover ◽  
Urban Land ◽  
Polarimetric Sar ◽  
Multiple Classifiers ◽  
Urban Land Cover ◽  
Object Based ◽  
Sar Data

Kajian Metode Klasifikasi Citra Landsat-8 untuk Pemetaan Habitat Bentik di Kepulauan Padaido, Papua

2017 ◽  
Vol 2 (1) ◽  
pp. 1 ◽  
Author(s):  
Muhammad Hafizt ◽  
Marindah Yulia Iswari ◽  
Bayu Prayudha
Keyword(s):  
Coral Reefs ◽  
Satellite Remote Sensing ◽  
Satellite Images ◽  
Habitat Mapping ◽  
Benthic Habitat ◽  
Landsat 8 ◽  
Classification Methods ◽  
Landsat 8 Oli ◽  
Remote Sensing Technique ◽  
Object Based

<strong>Assessment of Landsat-8 Classification Method for Benthic Habitat Mapping in Padaido Islands, Papua.</strong> Indonesia is the biggest archipelagic country in the world with an area of coral reefs of 39,583 km.This area has to be managed effectively and efficiently utilizing satellite remote sensing technique capable of mapping of benthic habitat coverage, such as coral reefs, seagrasses, macroalgae, and bare substrates. The technique is supported by the availability of Landsat-8 OLI satellite images that have been recording the regions of Indonesia continuously every 16 days. This research was carried out in June 2015 in parts of Padaido Islands, Papua. This area was selected due to high coral reef damages. This study utilized Landsat-8 OLI to compare two classification methods, namely pixel based and object based methods using ‘maximum 2 likelihood’ (ML) and ‘example based feature extraction’ classifications, respectively, after water column correction (Lyzenga method).  The results showed that both methods produced benthic habitat maps with 7 class covers. The pixel-based classification resulted in a better overall accuracy (47.57%) in the mapping of benthic habitats than object-based classification approach (36.17%). Thus, the ML classification is applicable for benthic habitat mapping in Padaido Islands. However, the consistency of this method must be analyzed in many diffrent locations of Indonesian waters.

Fuel type mapping using object-based image analysis of DMC and Landsat-8 OLI imagery

2017 ◽  
Vol 33 (10) ◽  
pp. 1064-1083 ◽  
Author(s):  
A. Stefanidou ◽  
E. Dragozi ◽  
D. Stavrakoudis ◽  
I. Z. Gitas
Keyword(s):  
Image Analysis ◽  
Landsat 8 ◽  
Fuel Type ◽  
Landsat 8 Oli ◽  
Object Based Image Analysis ◽  
Type Mapping ◽  
Object Based

Estimates of subtropical forest biomass based on airborne LiDAR and Landsat 8 OLI data

2015 ◽  
Vol 39 (4) ◽  
pp. 309-321 ◽  
Author(s):  
XU Ting ◽  
◽  
CAO Lin ◽  
SHEN Xin ◽  
SHE Guang-Hui
Keyword(s):  
Forest Biomass ◽  
Subtropical Forest ◽  
Airborne Lidar ◽  
Landsat 8 ◽  
Landsat 8 Oli
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